Linking protein structural and functional change to mutation using amino acid networks
The function of a protein is strongly dependent on its structure. During evolution, proteins acquire new functions through mutations in the amino-acid sequence. Given the advance in deep mutational scanning, recent findings have found functional change to be position dependent, notwithstanding the c...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782487/?tool=EBI |
| _version_ | 1818715688303329280 |
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| author | Cristina Sotomayor-Vivas Enrique Hernández-Lemus Rodrigo Dorantes-Gilardi |
| author_facet | Cristina Sotomayor-Vivas Enrique Hernández-Lemus Rodrigo Dorantes-Gilardi |
| author_sort | Cristina Sotomayor-Vivas |
| collection | DOAJ |
| description | The function of a protein is strongly dependent on its structure. During evolution, proteins acquire new functions through mutations in the amino-acid sequence. Given the advance in deep mutational scanning, recent findings have found functional change to be position dependent, notwithstanding the chemical properties of mutant and mutated amino acids. This could indicate that structural properties of a given position are potentially responsible for the functional relevance of a mutation. Here, we looked at the relation between structure and function of positions using five proteins with experimental data of functional change available. In order to measure structural change, we modeled mutated proteins via amino-acid networks and quantified the perturbation of each mutation. We found that structural change is position dependent, and strongly related to functional change. Strong changes in protein structure correlate with functional loss, and positions with functional gain due to mutations tend to be structurally robust. Finally, we constructed a computational method to predict functionally sensitive positions to mutations using structural change that performs well on all five proteins with a mean precision of 74.7% and recall of 69.3% of all functional positions. |
| first_indexed | 2024-12-17T19:07:20Z |
| format | Article |
| id | doaj.art-7da4edeb488c4ba78ec279534febaaab |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-17T19:07:20Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-7da4edeb488c4ba78ec279534febaaab2022-12-21T21:35:58ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01171Linking protein structural and functional change to mutation using amino acid networksCristina Sotomayor-VivasEnrique Hernández-LemusRodrigo Dorantes-GilardiThe function of a protein is strongly dependent on its structure. During evolution, proteins acquire new functions through mutations in the amino-acid sequence. Given the advance in deep mutational scanning, recent findings have found functional change to be position dependent, notwithstanding the chemical properties of mutant and mutated amino acids. This could indicate that structural properties of a given position are potentially responsible for the functional relevance of a mutation. Here, we looked at the relation between structure and function of positions using five proteins with experimental data of functional change available. In order to measure structural change, we modeled mutated proteins via amino-acid networks and quantified the perturbation of each mutation. We found that structural change is position dependent, and strongly related to functional change. Strong changes in protein structure correlate with functional loss, and positions with functional gain due to mutations tend to be structurally robust. Finally, we constructed a computational method to predict functionally sensitive positions to mutations using structural change that performs well on all five proteins with a mean precision of 74.7% and recall of 69.3% of all functional positions.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782487/?tool=EBI |
| spellingShingle | Cristina Sotomayor-Vivas Enrique Hernández-Lemus Rodrigo Dorantes-Gilardi Linking protein structural and functional change to mutation using amino acid networks PLoS ONE |
| title | Linking protein structural and functional change to mutation using amino acid networks |
| title_full | Linking protein structural and functional change to mutation using amino acid networks |
| title_fullStr | Linking protein structural and functional change to mutation using amino acid networks |
| title_full_unstemmed | Linking protein structural and functional change to mutation using amino acid networks |
| title_short | Linking protein structural and functional change to mutation using amino acid networks |
| title_sort | linking protein structural and functional change to mutation using amino acid networks |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782487/?tool=EBI |
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